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| active | true |
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| title | Data Access |
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| Data AccessThis is a limited access data set. To request access please register an account on the NCTN Data Archive. After logging in, use the "Request Data" link in the left side menu. Follow the on screen instructions, and enter NCT00352534 when asked which trial you want to request. In step 2 of the Create Request form, be sure to select “Imaging Data Requested”. Please contact NCINCTNDataArchive@mail.nih.gov for any questions about access requests.
| Data Type | Download all or Query/Filter | License |
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Images, Segmentations, and Radiation Therapy Structures/Doses/Plans (DICOM, XX.X GB) << latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >> |
(Download requires NBIA Data Retriever) | | Tissue Slide Images (SVS, XX.X GB) | | Tcia button generator |
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| Tcia button generator |
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label | Search(Download requires Aspera plugin)
| | Clinical data (CSV) | | |
Click the Versions tab for more info about data releases.
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| title | Detailed Description |
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| Detailed DescriptionImage Statistics | Radiology Image Statistics | Pathology Image Statistics |
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Modalities |
| Number of Patients | 165 | Number of Studies |
| Number of Series |
| Number of Images |
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<< Add any additional information that didn't fit or belong in the Summary section. >>
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| Localtab |
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| title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy| Tcia limited license policy |
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| Info |
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| DOI goes here. Create using Datacite with information from Collection Approval form |
| Info |
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| title | Publication Citation |
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| Kujawa, A., Dorent, R., Connor, S., Thomson, S., Ivory, M., Vahedi, A., Guilhem, E., Bradford, R., Kitchen, N., Bisdas, S. and Ourselin, S., 2022. Deep Learning for Automatic Segmentation of Vestibular Schwannoma: A Retrospective Study from Multi-Centre Routine MRI. medRxiv. Wijethilake, N., Kujawa, A., Dorent, R., Asad, M., Oviedova, A., Vercauteren, T. and Shapey, J., 2022. Boundary Distance Loss for Intra-/Extra-meatal Segmentation of Vestibular Schwannoma. In International Workshop on Machine Learning in Clinical Neuroimaging (pp. 73-82). Springer, Cham. |
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| Required acknowledgements only (ex:The CPTAC program requests that publications using data from this program...). If they just want to thank someone, that goes in the Acknowledgement section underneath the Summary. |
| Info |
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| Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC.https://doi.org/10.1007/s10278-013-9622-7 |
Other Publications Using This DataTCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk. |
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| Version X (Current): Updated yyyy/mm/dd| Data Type | Download all or Query/Filter | License |
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Images, Segmentations, and Radiation Therapy Structures/Doses/Plans (DICOM, XX.X GB) << latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >> |
(Download requires the NBIA Data Retriever) | Tissue Slide Images (SVS, XX.X GB) | | Tcia button generator |
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| Tcia button generator |
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label | Search | | | Clinical data (CSV) | | |
<< One or two sentences about what you changed since last version. No note required for version 1. >> |
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